A surge in artificial intelligence spending by the world’s largest technology companies has reignited fears of an AI investment bubble, after investors reacted sharply to the scale of planned capital expenditure. But according to Nigel Green, CEO of global financial advisory group deVere, those concerns are largely short-sighted and overlook the long-term strategic logic behind the spending.

Major tech firms including Amazon, Google, Microsoft and Meta have revealed plans to collectively invest around $660billion in AI-related infrastructure this year, a dramatic increase from roughly $410bn last year. The spending- largely directed towards data centres, advanced chips and cloud infrastructure- represents a jump of around 60% and rivals the annual economic output of some mid-sized countries.

Amazon has led the charge, warning that its capital expenditure could reach $200bn in 2026 alone, around $50bn more than market expectations. That announcement, alongside similar commitments from its peers, triggered a sell-off in tech stocks, wiping hundreds of billions of dollars from market capitalisations and reviving familiar questions about whether the AI arms race has become excessive.

Green acknowledges that investor unease is understandable, particularly as scrutiny around AI profitability intensifies. However, he argues the market is framing the issue incorrectly.

“The size of the number is what unnerves people, but the framing is wrong,” he says. “This is not capital being sunk into a single product that must quickly justify itself. What’s being built is a foundational layer that underpins everything these companies do, and will do in the future.”

Unlike traditional product investments, much of the AI spending is concentrated upfront but directed toward long-lived infrastructure. While the cash outlay is immediate, the accounting impact is spread across many years, meaning the true cost, and benefit, unfolds over time.

Crucially, Green argues that expecting AI to deliver a neat, standalone revenue stream misses the point. “AI doesn’t need to show up as a separate line item to generate returns,” he says. “Its value emerges through stronger customer retention, greater pricing power and lower churn across existing platforms.”

Nowhere is this clearer than in cloud computing. As AI workloads mature, they tend to lock customers into ecosystems and command higher-value, longer-term contracts. Over time, this supports margin expansion rather than erosion. Cloud platforms are already among the most profitable segments in tech, and AI only deepens their competitive advantage.

Green also highlights that a portion of the spending is defensive. “Maintaining relevance requires scale,” he notes. “The market may dislike the escalation, but for these companies, standing still isn’t an option.”

While volatility reflects uncertainty over timing and near-term returns, Green draws parallels with earlier waves of infrastructure investment that were initially questioned but later proved foundational. “This phase of AI investment is laying the groundwork for earnings power for many years,” he concludes, adding that underinvesting may ultimately be the greater risk for tech’s biggest players.

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